
import pandas as pd
import plotly.express as px
import matplotlib.pyplot as plt
import plotly.graph_objects as go


df = pd.read_csv("Estonian citizens abroad.csv",
                 header=0)
df.head()


target = df["# of Estonian citizens"]
target_label = "# of Estonian citizens"

name = df["Name"]
name_label = "Name"

df["Name and number of citizens"] = name.map(str) + '\n' + target.map(str)
name_target = df["Name and number of citizens"]
name_target_label = "Name and number of citizens"


# normalize distances

distance = df["Distance between Capital and Tallinn (km)"]


distance_norm = (distance-distance.min())/ (distance.max() - distance.min())

df["Distance normalized"] = distance_norm


fig = go.Figure(go.Scattergeo(
    text = df[name_target_label],
        lat = df["Latitude (capital)"],
        lon = df["Longitude (capital)"],
        marker = dict(
        size = df[target_label]**0.36,
        color = df[target_label],
        colorscale = "plasma",
        colorbar_title= target_label
        )
))
fig.update_geos(
    visible=False, resolution=50,
    showcountries=True, projection_type="natural earth",
    showland=True, landcolor="LightBlue"
)
fig.update_traces(customdata=df[name_target_label])
fig.update_traces(hovertemplate='%{customdata}<extra></extra>')

fig.show()


fig = px.scatter(df, x="Distance normalized", y = target_label,
                 color = "Continent",
                 log_y = True,
                 hover_name = "Name",
                 hover_data = {"Distance normalized":False,
                               "Continent":False,
                               target_label:":.0f"},
                 labels = {target_label: "# of Estonian citizens",
                            "Distance normalized": "Distance between country capital and Tallinn (normalized)"},
                )
fig.show()


# normalize GDP PPP per capita
GDP = df["GDP PPP per capita"]
GDP_norm = (GDP-GDP.min())/ (GDP.max() - GDP.min())

df["GDP PPP per capita normalized"] = GDP_norm
df.sort_values(by="GDP PPP per capita normalized", ascending = False)


fig = px.scatter(df, 
                 x="GDP PPP per capita", y = target_label,
                 color = "Continent",
                 log_y = True,
                 hover_name = "Name",
                 hover_data = {"GDP PPP per capita":":.0f",
                               "Continent":False,
                               target_label:False
                              },
                 labels = {
                     target_label: "# of Estonian citizens",
                     "GDP PPP per capita": "GDP PPP per capita (INT USD, 2020)"
                 }
                )
fig.show()

	Nimi	Name	iso_alpha	# of Estonian citizens	Continent	Sub-region	Capital	Latitude (capital)	Longitude (capital)	Distance between Capital and Tallinn (km)	Population (2020)	GDP PPP per capita	Formerly part of the USSR?	Sovereignty
0	Venezuela	Venezuela	VEN	237	Americas	South America	Caracas	10.500000	-66.933300	9098.0	28435943	NaN	No	Sovereign
1	Monaco	Monaco	MCO	28	Europe	Western Europe	Monaco	43.739600	7.406900	2103.1	39244	NaN	No	Sovereign
2	Taiwan (Chn)	Taiwan	TWN	12	Asia	Eastern Asia	Taipei	25.047800	121.531900	7996.5	23816775	NaN	No	Sovereign
3	Jersey (Gbr)	Jersey	JEY	5	Europe	Northern Europe	Saint Helier	49.185800	-2.110000	2059.7	107800	NaN	No	Not sovereign
4	Ühendriikide Hajasaared (Usa)	United States Minor Outlying Islands	UMI	5	Oceania	Micronesia	Wake Atoll	19.308552	166.631012	10598.8	300	NaN	No	Not sovereign

	Nimi	Name	iso_alpha	# of Estonian citizens	Continent	Sub-region	Capital	Latitude (capital)	Longitude (capital)	Distance between Capital and Tallinn (km)	Population (2020)	GDP PPP per capita	Formerly part of the USSR?	Sovereignty	Name and number of citizens	Distance normalized	GDP PPP per capita normalized
19	Luksemburg	Luxembourg	LUX	280	Europe	Western Europe	Luxembourg	49.610600	6.132800	1613.6	625976	117500.20720	No	Sovereign	Luxembourg\n280	0.089800	1.000000
20	Singapur	Singapore	SGP	33	Asia	South-eastern Asia	Singapore	1.300000	103.800000	9266.5	5850343	98520.02954	No	Sovereign	Singapore\n33	0.538738	0.836736
21	Iirimaa	Ireland	IRL	2469	Europe	Northern Europe	Dublin	53.349700	-6.260300	2002.8	4937796	93180.94540	No	Sovereign	Ireland\n2469	0.112632	0.790810
22	Katar	Qatar	QAT	8	Asia	Western Asia	Doha	25.300000	51.533300	4324.3	2881060	89968.77102	No	Sovereign	Qatar\n8	0.248816	0.763180
23	Bermuda (Gbr)	Bermuda	BMU	3	Americas	Northern America	Hamilton	32.294200	-64.783900	6936.5	62273	80829.61681	No	Not sovereign	Bermuda\n3	0.402054	0.684566
...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...
14	Ahvenamaa	Åland Islands	ALA	1	Europe	Northern Europe	Mariehamn	60.098600	19.944400	279.1	30129	NaN	No	Not sovereign	Åland Islands\n1	0.011515	NaN
15	Antarktis	Antarctica	ATA	1	Antarctica	Antarctica	NaN	-75.250973	-0.071389	15251.9	4877	NaN	No	Not sovereign	Antarctica\n1	0.889856	NaN
16	Réunion (Fra)	Réunion	REU	1	Africa	Eastern Africa	Saint-Denis	-20.878900	55.448100	9359.0	895308	NaN	No	Not sovereign	Réunion\n1	0.544164	NaN
17	Svalbard ja Jan Mayen (Nor)	Svalbard and Jan Mayen	SJM	1	Europe	Northern Europe	Longyearbyen	78.216700	15.633300	2114.0	2939	NaN	No	Not sovereign	Svalbard and Jan Mayen\n1	0.119155	NaN
18	Wallis ja Futuna (Fra)	Wallis and Futuna	WLF	1	Oceania	Polynesia	Mata-Utu	-13.282500	-176.173600	14600.7	11246	NaN	No	Not sovereign	Wallis and Futuna\n1	0.851655	NaN